{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "5e9ec21dbc1344f795b0b6d0f2efd199",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Models:   0%|          | 0/6 [00:00<?, ?model/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "5cf5908520454a868a0fe3c0fbd13185",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "o4-mini/val:   0%|          | 0/1 [00:00<?, ?file/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "05f52ba70bab423ea8e2d3e57f0497a7",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "gpt-4.1/val:   0%|          | 0/1 [00:00<?, ?file/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "6abdd7bd04884205bf2fd3376912da11",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "gpt-4o/val:   0%|          | 0/1 [00:00<?, ?file/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "d0de0529d04d42078e5f532b456281be",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "o3/val:   0%|          | 0/1 [00:00<?, ?file/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "e82a7c8e402f45f890412b1ac430f8d1",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "sonnet-4/val:   0%|          | 0/1 [00:00<?, ?file/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "c7649c6166bb4a2da80b97d321be4a64",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "gpt-4o-mini/val:   0%|          | 0/1 [00:00<?, ?file/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import importlib\n",
    "import os\n",
    "\n",
    "from dotenv import load_dotenv\n",
    "\n",
    "import art.utils.benchmarking.charts\n",
    "from art.utils.benchmarking.charts import (\n",
    "    percentage_comparison_bar_chart,\n",
    "    training_progress_chart,\n",
    ")\n",
    "from art.utils.benchmarking.load_trajectories import load_trajectories\n",
    "from art.utils.benchmarking.types import BenchmarkModelKey\n",
    "from art.utils.get_repo_root_path import get_repo_root_path\n",
    "from art.utils.s3 import pull_model_from_s3\n",
    "\n",
    "importlib.reload(art.utils.benchmarking.charts)\n",
    "\n",
    "load_dotenv()\n",
    "\n",
    "project_name = \"mcp_balldontlie\"\n",
    "\n",
    "PULL_MODELS = True\n",
    "if PULL_MODELS:\n",
    "    await pull_model_from_s3(\n",
    "        model_name=\"mcp-010\",\n",
    "        project=project_name,\n",
    "    )\n",
    "    await pull_model_from_s3(\n",
    "        model_name=\"gpt-4o-mini\",\n",
    "        project=project_name,\n",
    "    )\n",
    "    await pull_model_from_s3(\n",
    "        model_name=\"gpt-4o\",\n",
    "        project=project_name,\n",
    "    )\n",
    "    await pull_model_from_s3(\n",
    "        model_name=\"gpt-4.1\",\n",
    "        project=project_name,\n",
    "    )\n",
    "    await pull_model_from_s3(\n",
    "        model_name=\"o3\",\n",
    "        project=project_name,\n",
    "    )\n",
    "    await pull_model_from_s3(\n",
    "        model_name=\"o4-mini\",\n",
    "        project=project_name,\n",
    "    )\n",
    "    await pull_model_from_s3(\n",
    "        model_name=\"sonnet-4\",\n",
    "        project=project_name,\n",
    "    )\n",
    "\n",
    "df = await load_trajectories(\n",
    "    project_name=project_name,\n",
    "    models=[\"mcp-013\", \"gpt-4o-mini\", \"gpt-4o\", \"gpt-4.1\", \"o3\", \"o4-mini\", \"sonnet-4\"],\n",
    ")\n",
    "\n",
    "benchmarks_dir = f\"{get_repo_root_path()}/assets/benchmarks/{project_name}\"\n",
    "\n",
    "os.makedirs(benchmarks_dir, exist_ok=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1800x1200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "line_graph = training_progress_chart(\n",
    "    df,\n",
    "    \"success\",\n",
    "    models=[\n",
    "        BenchmarkModelKey(\"mcp-010\", \"mcp-010\", \"val\"),\n",
    "        BenchmarkModelKey(\"gpt-4o-mini\", \"GPT-4o-mini\"),\n",
    "        BenchmarkModelKey(\"gpt-4o\", \"GPT-4o\"),\n",
    "        BenchmarkModelKey(\"gpt-4.1\", \"GPT-4.1\"),\n",
    "        BenchmarkModelKey(\"o3\", \"o3\"),\n",
    "        BenchmarkModelKey(\"o4-mini\", \"o4-mini\"),\n",
    "        BenchmarkModelKey(\"sonnet-4\", \"Sonnet-4\"),\n",
    "    ],\n",
    "    title=\"Success Rate over Time\",\n",
    "    y_label=\"Success Rate\",\n",
    ")\n",
    "line_graph.savefig(f\"{benchmarks_dir}/accuracy-training-progress.svg\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1800x1200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bar_chart = percentage_comparison_bar_chart(\n",
    "    df,\n",
    "    metric_name=\"beat_comp\",\n",
    "    models=[\n",
    "        BenchmarkModelKey(\"mcp-010\", \"mcp-010\", \"val\"),\n",
    "        BenchmarkModelKey(\"gpt-4o-mini\", \"GPT-4o-mini\"),\n",
    "        BenchmarkModelKey(\"gpt-4o\", \"GPT-4o\"),\n",
    "        BenchmarkModelKey(\"gpt-4.1\", \"GPT-4.1\"),\n",
    "        BenchmarkModelKey(\"o3\", \"o3\"),\n",
    "        BenchmarkModelKey(\"o4-mini\", \"o4-mini\"),\n",
    "        BenchmarkModelKey(\"sonnet-4\", \"Sonnet-4\"),\n",
    "    ],\n",
    "    title=\"Win Rate\",\n",
    ")\n",
    "bar_chart.savefig(f\"{benchmarks_dir}/accuracy-comparison.svg\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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9FOpSbW/+mG9+BTsAAA2PtiEAAI1I3LBu2WWXDZMmTcpex40AYy/l2JIitp/Ir5CuNLyO8y6//PJZb+Rozpw5YdiwYWHrrbfOxqq2eIh9qHv27Fmr31dTFHs+x7A5bpBZ1YUXXhh69+4d1lxzzYrmuf7668Pll19e9NiKK66YtZXp0aNHWGONNbI5Y3BddWPL2GakLsXWNfluvPHGsM0229Tp+wIAkD6V1wAAjUhsNbHZZpvljL355pvZf2PYPGPGjAXj3bp1y0LtSufNb0kS21BE+YF43KixMbbzqG9x08vY3qNNmzY54/GXEHEDx0oqimNbkFg9na9///5Z25DYRiZWZf/hD38Ie+21V7axYdXgOqr6b6a+Nt3U6gMAgEh4DQDQyOSHzPMrdxe1tUd+lXbc8K9YaxItQ2pPrIaOmzfme/fdd7MWItUZOHBgmD17ds5YDKpjKB6rrSsxv9q+rnTq1KlgbMyYMXX6ngAANAzCawCARqZUhXR+eB1bftREDKWrbiJYKrzOf38WTdxkcf311y8Yv+GGG3LatRTz1FNP5byOlfb/9V//VaP3f//99wvG5s6dG2pLx44dw2qrrZYzll/NX6mPP/443H333eG5554LH374YbWbUQIAkDbhNQBAI9OlS5ecatbYOiK2fpgfYketW7cOffr0qXHIuNZaay14PW7cuPD1119nVcDzrb766tn7U3tiC5bzzz+/oBVL3Ojw7LPPLnndlClTwrfffpszFnuR17Sly+DBgwvG8qu5F1Xs4V3Vq6++ulC9tmN/73PPPTfb7HK33XYLG220Uc6/ewAAGhbhNQBAI1S1+jlWn/7rX//KeiXPt8kmm4S2bdvWeN781iGPPPJIFqLOp2VI3VhvvfXCb37zm4LxGPIOGjSo6DXFemJX/TdQieeffz688sorBeNV/86LqWlAvs8+++S8jhuCltpkspQPPvggPPzwwzlj8Zc4sY83AAANk/AaAKAR2mKLLXJe33HHHWVD6ErlX/fQQw/lvBZe153Y+3rllVcuGI/9qydOnFgwvuyyy4ZWrVrljMXWMcXOLSZW7J9yyilFj1W3iWOs7K9q+vTp1VZe/+xnP8sZixtKxp7dlYi/oImbWMbQu6pDDz20ousBAEiT8BoAoJGG18X6Uy9qeB1DxqoV21X7Ibds2TJsvvnmCzUv1VtyySXDWWedVTA+efLk8Kc//algvHnz5mGzzTYrCHnjho1Tp04t+T6xJUjsGz1gwIBs7mKmTZtW9l47dOiQ8zr2n67O6aefXhC2X3DBBeGiiy4q+36xvUjsCz5q1Kic8dhH+4ADDqj2fQEASFfLxX0DAADUvuWWWy7rT50f6M3vXb3OOuss1LyxojYG2C+88ELBsdieYamlllqoealMv379wg477BCefvrpnPEHH3ww7LXXXgVhdWw1MnTo0Jyxl156Key6665h3333zXpCx38rMbCOPcyHDRsWHn/88fDFF1/kXNOuXbuczQ/Hjx9f9j7jxpBfffXVgtf3339/6Ny5c9Znfd68eVnbkdi6pqpYeX3yySdnYXVVt912W9aeZvfdd8++v/jvN/r888+zf4f//Oc/CyrB47/Tyy67rKACHACAhkV4DQDQiPteFwuvF7bquur1xcJrLUPqR6y+fvnll3PC5Chu3hh7PlcNbLfffvts48IY8FYVg+Wrrrqq2veKVfbnnHNOeP3118N99923YPytt94qe93GG2+cBeHzxbC6anV4DKDzQ/X5bT5iX+7Y7zqG3PNNmDAh3H777dlXddq0aZNdv8EGG1R7LgAAadM2BACgifS9rs3wui7mpTKxqvmEE04oGP/444/D9ddfXzB+8cUXh1122aXG7xOrnGNFd//+/UPPnj0LNkccO3ZsyWt/+9vfLqiQLiZWbpfqvX300UdnwXqx/t7V6dGjR9bfPYb2AAA0fMJrAIBGatNNNy3oIRz7YMeK7EXRvXv3gmAx9jjODzipOwcffHDR1i833HBDGD16dM5YrMSOlcixjUZ1f0exr3bfvn3DTTfdlG2WuMYaa2TjO+20U8G/pfxNQPM3i/zb3/6WtSUptyFkufYogwcPDmeeeWZYf/31c/q3FxO/r/PPPz8L22P7GgAAGodm86o+jwcAADRqsWXIiBEjsv/GjRtjm43Y9zpucBhbbcSNN2tTDKljm5HY+iNq37591v869rheeumlK5ojVmnHe/7mm2/CpEmTspYicZ5YhR6D63j/AAA0PsJrAAAAAACSo20IAAAAAADJEV4DAAAAAJAc4TUAAAAAAMkRXgMAAAAAkBzhNQAAAAAAyRFeAwAAAACQHOE1AAAAAADJEV4DAAAAAJAc4TUAAAAAAMkRXgMAAAAAkBzhNQAAAAAAyRFeAwAAAACQHOE1AAAAAADJEV4DAAAAAJAc4TUAAAAAAMkRXgMAAAAAkBzhNQAAAAAAyRFeAwAAAACQHOE1AAAAAADJEV4DAAAAAJAc4TUAAAAAAMkRXgMAAAAAkBzhNQAAAAAAyRFeAwAAAACQHOE1AAAAAADJEV4DAAAAAJAc4TUAAAAAAMkRXgMAAAAAkBzhNQAAAAAAyRFeAwAAAACQHOE1AAAAAADJEV4DAAAAAJAc4TUAAAAAAMkRXgMAAAAAkBzhNQAAAAAAyRFeAwAAAACQHOE1AAAAAADJEV4DAAAAAJAc4TUAAAAAAMkRXgMAAAAAkJyWi/sGAAAAACoxb9688Pbbb4f33nsvTJw4MbRt2zasuuqqoU+fPqFDhw4LPe9XX30V7rvvvpyxTp06hb333rsW7hoaNuuOxUl4DQAAAI3Qp59+GoYMGRKGDh2a/XnChAlh5syZWdjUrVu30Lt377D77ruH7t27Vzzn2muvXWf3e/zxx4cTTjih5PGHH344XH755WHs2LEFx1q0aBF22223cNJJJ4WVV165xu99ww03hDvvvDNn7MILL6zxPGDdVc66oxLN5sVfnwAAAACNwrhx48Jf//rX8I9//CPMmTOn2vO33377cMYZZ4TVVlstyRAtxhbnn39+QchVTMeOHcONN94Y1l133RpVf/br1y8LGOfr3LlzeOKJJ0LLlmr+qIx1Z91RN/S8BgAAgEbi1VdfDb/85S/DoEGDKgrQomeeeSa7JoZGKRo4cGBFAVo0fvz4cOyxx4apU6dWPH8M3aoGaNHRRx8tQKNi1p11R90RXgMAAEAj8Oyzz4bDDz88TJ48ucbXfv/99+H3v/99eOihh0JK4vdy2WWXFYyvssoq4aCDDgqbb755wbEvvvgiXHvttRXN//XXXxftudu/f/9FuGuaEuvuR9YddUV4DQAAAA3cmDFjwsknnxxmzZq10HPMnTs3nHnmmeG1114LqYj9dqdPn54zttRSS4V77703/PGPfwy333572HXXXQuuixWwlfwsbrrppjBjxoycsd/+9rehVatWtXD3NHbWXS7rjrogvAYAAIAGLoZfU6ZMKXl8pZVWCltttVXYaKONygZEs2fPDv/v//2/gmCpPnTp0qVg7Pnnny8Y22mnnbLvZ74DDzyw4JyJEyeGd999t+z7ffPNN1kYl19Zus8++9TwzmmqrLtc1h11QXgNAAAADdjLL79csmpziSWWCBdddFF47rnnws033xzuueee7M8777xzyfnGjh0b7rrrrlCfYtuFYi0D3nnnnYKxDTbYIOf1euutV3TOt99+u9rqzx9++KGg+rN169YV3jVNmXVn3VE/dEEHAACABiy/irGq888/P+y55545Y8svv3y4/PLLw2mnnVay127cqO3QQw8NzZvn1ryNGjVqoe4xbmJ38MEHFw37+vbtm1Wd5otVqBMmTCgYr1r9GbVr1y5raZC/Wdy4ceNK3k+cNwaKVa244oph3333rej7AevOuqN+qLwGAACABmrevHnhpZdeKnqsa9euBQHafM2aNQtnn312FqiVqgKtzR68V155ZdH5VltttXDJJZdk95MvPxSrGprla9u2bcXXz6/+zO/pq/qTSll3P7LuqA/CawAAAGigRo8eHSZNmlT02JZbbln22hhGFWsZMN8zzzwTaqu9wvXXX18w3qJFi/CXv/wltG/fvmQf4GKKBW4tWxY+WF5q47jYlze/+rNjx45h//33L/k9QFXW3Y+sO+qD8BoAAAAaqK+//rrksdVXX73a6zfddNOSx15//fWwqKZNmxZOPfXUMHfu3IJjRxxxRNhwww1LXlus0rNUOFZso7sll1yy6PWxB/H3339fcC+xTzFUwrr7kXVHfRBeAwAAQANVqvqzXIhU1corr1zy2Lvvvpv1zF0Uf/3rX4v2wI0B3wknnFD22nj/xSo787/nGNB99913BectvfTSRas/77777pyx2MLhgAMOKHsvUJV1Z91Rf4TXAAAA0AjNnDmz2nPK9ZqN13/xxRcL/f4xhIsb0BVz5plnVtvnNm5a171794LxTz75JOd1vMdirQ7WWmutgrFbb721oPrz8MMPL9q7FxaGdWfdUbuE1wAAANBALbPMMiWPjR8/fpEqSKPPPvssLKxzzz23aAXp9ttvH7bddtuK5ujVq1fB2NChQ3Nev/jii0X78/bs2TNnbPLkyeGuu+7KGVt22WXDgAEDKroXmM+6s+6oP8JrAAAAaKBWXHHFkseGDx9e7fVvv/122eMTJkxYqPsaMmRIGDZsWNGqzpNOOqnieXbfffei39dVV10Vvv322/Daa6+FK664ouCcLbbYouBnE6s/Yy/g/OrPUj1+oRTrzrqj/givAQAAoIFac801S1aBvvLKK+Hzzz8veW3sWTto0KCy88eqyZqaN29e0WAr2m233UKPHj0qnqtPnz5ho402Khi/8sors2MHHnhg0UrXI488Mud1DNzyWynEn1u8HmrKurPuqD/CawAAAGig4mP6m222WdFjsXXAqaeeGqZPn15yU7dRo0aVnf+HH36o8T09/vjj4b333ita/VndZnHFXHLJJWXbNOQ79NBDswrQqm677bYwderUnLFDDjmkos31IJ91V8i6o64IrwEAAKABK9c7Nj7ev99++4XBgwdnVZAzZswII0aMCCeeeGK47rrrqp171qxZNb6fG2+8sej4DjvsEFZfffUazxevufvuu0O3bt3KnteyZctwzDHHhNNPPz1n/Lvvvgt33HFHztjSSy8dDj744BrfC8xn3f3IuqOutazzdwAAAADqzOabbx422WST8Prrrxc9/v7774fjjz++Xu7ljTfeCCNHjixZmbkobRoeeeSR8PDDD4cnn3wyvPvuu2HixImhdevWYZVVVskqPg844IDsvHy33357mDJlSs5YDNCWWmqphb4fsO6sO+qH8BoAAAAauPiI/1577VUQFi2qVq1a1ej8u+66q+j4WmutFTbddNNFupdY4bn33ntnX5WKP4+BAwfmjLVv375o9WfsGRwDusceeyyrko2b5sWWC3EDuo033jjsueeeBW0RaNqsu+KsO2qT8BoAAAAauC5duoS//OUvWW/b2KKgUsstt1zWf/azzz4rerxNmzYVzxVDpyeeeKLosf79+4fFIVZ/xvYFVR100EGhQ4cOOWPjxo3LfnYxPMs3ZsyY7CtusrfddtuFP//5z1kQB9ZdcdYdtUnPawAAAGgEtt1223DLLbdUvMlaDJJuuummsMIKK5Q8pyYbtv3rX/8q2qu3RYsWYY899gj1LW4Ul1/9GQPD/DYKsQ3C/vvvXzRAy/fss89mIVxNgkoaN+sul3VHbRNeAwAAQCPRu3fv7PH7fffdN3vcv5Sf//znWR/b9ddfP0yfPr1shWil4vuWuqfYAqC+xQAtbpZX1W9+85ts07iq/ud//ierAK1U7Pt72WWX1dp90vBZdz+x7qhtzebF5jIAAABAozJ58uTwzDPPhPfeey988803YYkllgidO3cOO+64Y+jRo8eC83bYYYcwduzYonPEXrSrr756te/11VdfZRWoxSKG0047LRx22GGhvqs/+/btm/0M5mvXrl14+umnw7LLLrtgbPTo0WGXXXYpuH7AgAHZZntxnjPOOCO89tprOcfbtm0bnn/++YI2CGDdWXfULj2vAQAAoBGKrQfiZnLlxNBr/PjxJTeN69SpU0XvNXjw4KIBWhT71da3O++8MydAmx+MVQ3QokcffbTg2lVXXTX88Y9/zNouLL/88uHiiy8O/fr1yzknVs0+9dRTNdrEjqbBurPuqF3ahgAAAEAT9eWXX4aZM2cWPbb22muXbYFQ1UsvvVR0PIZwa6yxRqhP06ZNC7feemtBxeYRRxxRcO7w4cMLxrbYYossQKu6Kd9qq61W0bVQCevOuqNywmsAAABoZGKF4pgxY6o9r9xmaRtttFHF7/f6668XHd94441DfbvrrrsKqj9//etfF+0jHNsX5CvWrqFYiFbsWpo26866o/ZpGwIAAAANWHyMPvaBjZufzf+av2HaCy+8UHbTttiLtpTtt9++ovf/6KOPwqRJk4oe22STTUJ9+v7778Mtt9ySM9amTZui1Z/Rd999VzBWrJ9u+/btK7qWpsO6+4l1R10SXgMAAEAD9sknn4R777236LEhQ4Zk1Y/FxArRxx57rOixFVZYIfTp06ei93/jjTdKHuvVq1eo7+rP/EBvv/32y76fUpWyxXoO52vdunXRwI6my7r7iXVHXdI2BAAAABqwTTfdtOSxa665JqsIzffVV1+Fo446qmTf3f33379omFRMqcf4Y//a7t27h/oSA7H86s8lllgi/Pa3vy15TezJm2/WrFkFY8V+Tu3atVvoe6Xhs+5+ZN1R11ReAwAAQAO24YYbhq5duxbttfv111+HPfbYIxx++OHZebGS8bXXXgu33XZbQX/a+ZZZZplw2GGHVfz+pXr8xnsqVjlZV+6+++4wceLEnLF99923bPuG2Kpg6tSp1bYlmDJlStFrabqsux9Zd9Q14TUAAAA0cAceeGC44IILih6LodDll19e8VxnnXVW0V6z5donFFNss7W6rP68+eabc8ZiBWu56s+oW7du4Ysvvqg2FCw2Fq+labPurDvqnrYhAAAA0MANGDAgrLXWWos8T6z83H333Wt0zZdffll0fOWVVw715Z577gkTJkzIGfvVr35V7T0U6w384osvhtmzZ+e0Z/j8888rupamxbqz7qh7wmsAAABo4Fq2bBmuuOKKsPzyyy9SgHbqqafW6Jq5c+eW3EBtpZVWCvXhhx9+KFr9eeSRR1Z7bbHAMPYqPuecc7JQLlZ+nn766UV79vbr128R75yGzrqz7qh7wmsAAABoBNZYY40wcODAGleCxl67f/nLX8Jpp50WmjVrVqNrSwVo9bmxWqz+HD9+fM7YXnvtFVZdddVqr40tCHbccceC8fvvvz9sueWW4Re/+EV48803i26sp/cukXX3E+uOuiC8BgAAgEaie/fu4e9//3tWtdilS5ey53bu3Dn87ne/C0899VSNWxbMN23atJLHYpVkXZsxY0a46aabCqo/jzrqqIrnOPfcc2vUamGdddYJ//3f/12j+6Rxs+6sO+pOs3nz5s2rw/kBAACAxSQ+fv/222+Hb775JqvWbNOmTRYYrbfeeqFr166hoYsVr/kb5u2zzz7hwgsvrNE8sWXBCSecEEaMGFH2vG222Sb83//9X4021qPpse4qY91RCeE1AAAA0ODMnDkz9O3bN3z99dc5PYgfe+yxsNpqq9V4vhiPDB48ODz++ONZy4LYeze2c1hhhRXCxhtvHPbcc8+w1VZb1fJ3AQ2LdUd9E14DAAAAAJAcPa8BAAAAAEiO8BoAAAAAgOQIrwEAAAAASI7wGgAAAACA5AivAQAAAABIjvAaAAAAAIDkCK8BAAAAAEiO8BoAAAAAgOQIrwEAAAAASI7wGgAAAACA5AivAQAAAABIjvAaAAAAAIDkCK8BAAAAAEiO8BoAAAAAgOQIrwEAAAAASI7wGgAAAACA5AivAQAAAABIjvAaAAAAAIDkCK8BAAAAAEiO8BoAAAAAgOQIrwEAAAAASI7wGgAAAACA5AivAQAAAABIjvAaAAAAAIDkCK8BAAAAAEiO8BoAAAAAgOS0XNw3AAAAAI3F2E8/DHPnzFnct0Ej1LxFi9Bpte6L+zaSZe1RV6y9xUt4DQAAALUkhmdz5wrQoL5Ze9A4aRsCAAAAAEByhNcAAAAAACRHeA0AAAAAQHKE1wAAAAAAJEd4DQAAAABAcoTXAAAAAAAkR3gNAAAAAEByhNcAAAAAACRHeA0AAAAAQHKE1wAAAAAAJEd4DQAAAABAcoTXAAAAAAAkR3gNAAAAAEByhNcAAAAAACRHeA0AAAAAQHKE1wAAAAAAJEd4DQAAAABAcoTXAAAAAAAkR3gNAAAAAEByhNcAAAAAACRHeA0AAAAAQHKE1wAAAAAAJEd4DQAAAABAcoTXAAAAAAAkR3gNAAAAAEByhNcAAAAAACRHeA0AAAAAQHKE1wAAAAAAJEd4DQAAAABAcoTXAAAAAAAkR3gNAAAAAEByhNcAAAAAACRHeA0AAAAAQHKE1wAAAAAAJEd4DQAAAABAcoTXAAAAAAAkR3gNAAAAAEByhNcAAAAAACRHeA0AAAAAQHKE1wAAAAAAJEd4DQAAAABAcoTXAAAAAAAkR3gNAAAAAEByhNcAAAAAACRHeA0AAAAAQHKE1wAAAAAAJEd4DQAAAABAcoTXAAAAAAAkR3gNAAAAAEByhNcAAAAAACRHeA0AAAAAQHKE1wAAAAAAJEd4DQAAAABAcoTXAAAAAAAkR3gNAAAAAEByhNcAAAAAACRHeA0AAAAAQHKE1wAAAAAAJEd4DQAAAABAcoTXAAAAAAAkR3gNAAAAAEByhNcAAAAAACRHeA0AAAAAQHKE1wAAAAAAJEd4DQAAAABAcoTXAAAAAAAkR3gNAAAAAEByhNcAAAAAACRHeA0AAAAAQHKE1wAAAAAAJEd4DQAAAABAcoTXAAAAAAAkR3gNAAAAAEByhNcAAAAAACRHeA0AAAAAQHKE1wAAAAAAJEd4DQAAAABAcoTXAAAAAAAkR3gNAAAAAEByhNcAAAAAACRHeA0AAAAAQHKE1wAAAAAAJEd4DQAAAABAcoTXAAAAAAAkR3gNAAAAAEByhNcAAAAAACRHeA0AAAAAQHKE1wAAAAAAJEd4DQAAAABAcoTXAAAAAAAkR3gNAAAAAEByhNcAAAAAACRHeA0AAAAAQHKE1wAAAAAAJEd4DQAAAABAcoTXAAAAAAAkR3gNAAAAAEByhNcAAAAAACRHeA0AAAAAQHKE1wAAAAAAJEd4DQAAAABAcoTXAAAAAAAkR3gNAAAAAEByhNcAAAAAACRHeA0AAAAAQHKE1wAAAAAAJEd4DQAAAABAcoTXAAAAAAAkR3gNAAAAAEByhNcAAAAAACRHeA0AAAAAQHKE1wAAAAAAJEd4DQAAAABAcoTXAAAAAAAkR3gNAAAAAEByhNcAAAAAACRHeA0AAAAAQHKE1wAAAAAAJEd4DQAAAABAcoTXAAAAAAAkR3gNAAAAAEByhNcAAAAAACRHeA0AAAAAQHKE1wAAAAAAJEd4DQAAAABAcoTXAAAAAAAkR3gNAAAAAEByhNcAAAAAACRHeA0AAAAAQHKE1wAAAAAAJEd4DQAAAABAcoTXAAAAAAAkR3gNAAAAAEByhNcAAAAAACRHeA0AAAAAQHKE1wAAAAAAJEd4DQAAAABAcoTXAAAAAAAkR3gNAAAAAEByhNcAAAAAACRHeA0AAAAAQHKE1wAAAAAAJEd4DQAAAABAcoTXAAAAAAAkR3gNAAAAAEByhNcAAAAAACRHeA0AAAAAQHKE1wAAAAAAJEd4DQAAAABAcoTXAAAAAAAkR3gNAAAAAEByhNcAAAAAACRHeA0AAAAAQHKE1wAAAAAAJEd4DQAAAABAcoTXAAAAAAAkR3gNAAAAAEByhNcAAAAAACRHeA0AAAAAQHKE1wAAAAAAJEd4DQAAAABAcoTXAAAAAAAkR3gNAAAAAEByhNcAAAAAACRHeA0AAAAAQHKE1wAAAAAAJEd4DQAAAABAcoTXAAAAAAAkR3gNAAAAAEByhNcAAAAAACRHeA0AAAAAQHKE1wAAAAAAJEd4DQAAAABAcoTXAAAAAAAkR3gNAAAAAEByhNcAAAAAACRHeA0AAAAAQHKE1wAAAAAAJEd4DQAAAABAcoTXAAAAAAAkR3gNAAAAAEByhNcAAAAAACRHeA0AAAAAQHKE1wAAAAAAJEd4DQAAAABAcoTXAAAAAAAkR3gNAAAAAEByhNcAAAAAACRHeA0AAAAAQHKE1wAAAAAAJEd4DQAAAABAcoTXAAAAAAAkR3gNAAAAAEByhNcAAAAAACRHeA0AAAAAQHKE1wAAAAAAJEd4DQAAAABAcoTXAAAAAAAkR3gNAAAAAEByhNcAAAAAACRHeA0AAAAAQHKE1wAAAAAAJEd4DQAAAABAcoTXAAAAAAAkR3gNAAAAAEByhNcAAAAAACRHeA0AAAAAQHKE1wAAAAAAJEd4DQAAAABAcoTXAAAAAAAkR3gNAAAAAEByhNcAAAAAACRHeA0AAAAAQHKE1wAAAAAAJEd4DQAAAABAcoTXAAAAAAAkR3gNAAAAAEByhNcAAAAAACRHeA0AAAAAQHKE1wAAAAAAJEd4DQAAAABAcoTXAAAAAAAkR3gNAAAAAEByhNcAAAAAACRHeA0AAAAAQHKE1wAAAAAAJEd4DQAAAABAcoTXAAAAAAAkR3gNAAAAAEByhNcAAAAAACRHeA0AAAAAQHKE1wAAAAAAJEd4DQAAAABAcoTXAAAAAAAkR3gNAAAAAEByhNcAAAAAACRHeA0AAAAAQHKE1wAAAAAAJEd4DQAAAABAcoTXAAAAAAAkR3gNAAAAAEByhNcAAAAAACRHeA0AAAAAQHKE1wAAAAAAJEd4DQAAAABAcoTXAAAAAAAkR3gNAAAAAEByhNcAAAAAACRHeA0AAAAAQHKE1wAAAAAAJEd4DQAAAABAcoTXAAAAAAAkR3gNAAAAAEByhNcAAAAAACRHeA0AAAAAQHKE1wAAAAAAJEd4DQAAAABAcoTXAAAAAAAkR3gNAAAAAEByhNcAAAAAACRHeA0AAAAAQHKE1wAAAAAAJEd4DQAAAABAcoTXAAAAAAAkR3gNAAAAAEByhNcAAAAAACRHeA0AAAAAQHKE1wAAAAAAJEd4DQAAAABAcoTXAAAAAAAkR3gNAAAAAEByhNcAAAAAACRHeA0AAAAAQHKE1wAAAAAAJEd4DQAAAABAcoTXAAAAAAAkR3gNAAAAAEByhNcAAAAAACRHeA0AAAAAQHKE1wAAAAAAJEd4DQAAAABAcoTXAAAAAAAkR3gNAAAAAEByhNcAAAAAACRHeA0AAAAAQHKE1wAAAAAAJEd4DQAAAABAcoTXAAAAAAAkR3gNAAAAAEByhNcAAAAAACRHeA0AAAAAQHKE1wAAAAAAJEd4DQAAAABAcoTXAAAAAAAkR3gNAAAAAEByhNcAAAAAACRHeA0AAAAAQHKE1wAAAAAAJEd4DQAAAABAcoTXAAAAAAAkR3gNAAAAAEByhNcAAAAAACRHeA0AAAAAQHKE1wAAAAAAJEd4DQAAAABAcoTXAAAAAAAkR3gNAAAAAEByhNcAAAAAACRHeA0AAAAAQHKE1wAAAAAAJEd4DQAAAABAcoTXAAAAAAAkR3gNAAAAAEByhNcAAAAAACRHeA0AAAAAQHKE1wAAAAAAJEd4DQAAAABAcoTXAAAAAAAkR3gNAAAAAEByhNcAAAAAACRHeA0AAAAAQHKE1wAAAAAAJEd4DQAAAABAcoTXAAAAAAAkR3gNAAAAAEByhNcAAAAAACRHeA0AAAAAQHKE1wAAAAAAJEd4DQAAAABAcoTXAAAAAAAkR3gNAAAAAEByhNcAAAAAACRHeA0AAAAAQHKE1wAAAAAAJEd4DQAAAABAcoTXAAAAAAAkR3gNAAAAAEByhNcAAAAAACRHeA0AAAAAQHKE1wAAAAAAJEd4DQAAAABAcoTXAAAAAAAkR3gNAAAAAEByhNcAAAAAACRHeA0AAAAAQHKE1wAAAAAAJEd4DQAAAABAcoTXAAAAAAAkR3gNAAAAAEByhNcAAAAAACRHeA0AAAAAQHKE1wAAAAAAJEd4DQAAAABAcoTXAAAAAAAkR3gNAAAAAEByhNcAAAAAACRHeA0AAAAAQHKE1wAAAAAAJKfl4r4BqAtz5swJw4YNCx9++GGYPHlyaN++fejcuXPYdNNNQ7t27RZ63jjfY489ljO27rrrhn79+tXCXUPDZ+1B/bPuAACAxkp43YRddtll4brrrlvkebbbbrtw/fXXV3TurFmzwksvvRSeeuqpMGLEiDB+/Pjw7bffhmWWWSZ07NgxbLjhhmHHHXcMm2++eWjZsuVCfYC/6667wjXXXBMmTZpUcLx169Zh//33DyeccEJYeumlazz/n//85/DMM8/kjN1+++01noemzdqz9qh/1p11BwAANDzC6ybsvffeq9f3e/nll8N5550XPvroo4Jj8QN9/HrnnXfCPffcE3r06BHOOeec0Lt374rnnzlzZvjDH/4QBg8eXPacO+64IwwdOjTcfPPNoVOnThXPP3LkyIIP8ZtsskkWOkBNWHvWHvXPurPuAACAhkfP6ybs3Xffrbf3uummm8IhhxxS9EN8MR988EH4zW9+E2677bYaVYiV+xBf1ccffxxOPPHEMHv27Irnv+qqqwrGjj/++Iqvh/msPWuP+mfdWXcAAEDDI7xuoiZOnBi++uqrenmv+IjxpZdeWuPr5s2bFy666KJw5513VtSXc+DAgQXj3bp1ywKEnj17Fhx7++23w3333VfRvcTquKeffjpnbKONNgpbbrllRdfDfNaetUf9s+6sOwAAoGESXjdR9fX4dOzx+ac//WmR5ogf5uOH7nLuv//+7IN/VXGzqjh+xhlnhL/97W9h4403Lrju3nvvregerr766oKxY489tqJroSpr70fWHvXJuvuRdQcAADQ0wusmqr4+yF944YVlH1OOH7ZjJVe5Ppzx+gsuuKDs+zz//PMFY3vttVdYaqmlsj+3atUq27Sq2M9hwoQJZeeO5wwZMiRnLG6ytc0225S9Doqx9n5k7VGfrLsfWXcAAEBDI7xuouqj9+crr7wShg0bVvTYEksskT1WHT8g33rrrdnjyZdcckn2gbuYN954I7z66qtFj02bNi2MGTOmYHyDDTYo+3q+6ircYgVafoXbcccdV/YaKMXa+4m1R32x7n5i3QEAAA1Jy8V9A6RVhbbjjjsW3aRpYcTHl0v5wx/+EPbcc8+csf79+4cvv/wyXH755SXn69OnT8H4uHHjwty5cwvGV1555ZzXHTt2LDpvvL6UUaNGFWyItf7664ftttuu5DVQjrWXe30p1h61ybrLvb4U6w4AAEiNyusmaObMmWH06NFFj6233nq18h7xsednn3226LEll1wyHHDAAUWPHXTQQaFt27ZFjz3zzDNFH8eOVWjF5M9Tat6pU6eGUlSgUZusvVzWHvXBustl3QEAAA2J8LoJev/990v25IwVVrXhzTffDFOmTCl6bIsttght2rQpeiz264z9QIuJ8w0fPrxgfNasWUXPb9489593y5bFHzQodX38OT355JM5Y+uuu27o27dv0fOhOtZeZddbe9Qm666y6607AAAgRcLrJqjcxlW1VYU2YsSIksd69uxZ9tpevXqVPPbWW28VrWorVW1X1YwZM4qeV+r6a665pqAC7dhjjy15b1Ada6+y6609apN1V9n11h0AAJAiPa+boFIf5GN/zBVWWCHbcCpuPBU3hPrhhx/C8ssvH1ZZZZWw1VZbhXXWWWeRN8fq2rVr2Wu7detWo3mXXnrpoudOmjQp5/XkyZOLnlfs+g8//DA88cQTOWNrrbVW1h8VFpa1V/311h61zbqr/nrrDgAASJXwugkq9SG7WbNmYeedd84+wBdz6aWXZh+yTzrppNCvX7+y7/Hpp5+WPJa/qVS+lVZaqUbzxpChQ4cO4bvvvssZ/+STT0Lv3r2rvaf4Ab1YBVr+hlixAi3+jGBhWXu5rD3qg3WXy7oDAAAaEm1Dmpj4SPCoUaOKHvv6669LfoifL256FTdvOv7448P06dNLnjd27NiSx5ZZZpmy71HueKl5N9xww4KxoUOH5rx+8cUXC85p165d6N69e87YRx99FB577LGcsXhODDlgYVl7uaw96oN1l8u6AwAAGhrhdRPz+eefl9xUqiYGDx4cDjnkkILKr+oeV47at29fdu5S/TiLPRY93+67714wFh+Bvu+++7Lv9+mnnw4DBw4sOGe33XYr2NTq2muvVYFGrbP2cll71AfrLpd1BwAANDTC6yam3MZVNTV8+PBw6qmnFmzwNG3atDBr1qyS18XKr3Latm1b8ljckOr7778vGN9ll11Cly5dcsbmzJkTzjrrrOwx6mOOOabgutatW4fDDjssZ+zjjz8O//rXv3LG4mPjcX5YFNbeT6w96ot19xPrDgAAaIiE101MuU2lFkas7rrzzjtzxso9Wh21aNGi7PH8qrB8cUOtfG3atAmXXHJJWGKJJUKlTj755LDmmmsWVKDFAKCqo48+OjRvbqmwaKy9n1h71Bfr7ifWHQAA0BD5dNLElPsgHx9dPvLII8ODDz4Y3njjjfD6669nH9J/8YtflJ0zfvit+uF69uzZi/RBvboP+qUq3DbZZJNwyy23lN38av6H/rPPPjt7BDx/s6tHH300Z6xr165FH8+GmrL2rD3qn3Vn3QEAAA1b+U9UNDoTJ04sOr7RRhuFyy67LKyyyio545tuumn2ddttt4WLLrqo6LUTJkwIgwYNCgMGDMhe5/fOzFddRVd1x8vNHx+XfvLJJ8P999+fVch98MEHWS/S+Nh2p06dwtZbbx1+/etfF3yf5SrQqgsWoBLWnrVH/bPurDsAAKBhazYvv3kjjV7sgzlmzJis12X8ihtQ/f73v6+2L+dxxx0XnnrqqaLHtt1223DDDTdkf/7qq6/CNttsU3Ked955p+yH49jjs2fPniWPDx06NHTs2DHUpk8//TTr8Vm1gi72E3388ccLqubiOf/4xz+yDbxiVV8MR+Kj27H6rU+fPmGvvfYKG264Ya3eH42DtVfI2qOuWXeFrDuAuvXZx6PC3Lm5vyCE2tC8eYvQZY21F/dtJMvao65Ye4uXyusmKH5gX2+99bKvmjj88MNLfpB/7bXXsg+48UNvq1atys4TK73KfZDPrwTLFzedqm2xAi3/0e9YgZb/If79998PJ5xwQhaE5IcPU6ZMCR9++GH429/+Fvbee+9wzjnn1Mm90nBZe4WsPeqadVfIugMAABoKPa+p2M9+9rPQtm3bosemTZuWVZ9FSy21VNl54ofehenvGTVr1qza+Wvqs88+Cw8//HDOWHzcun///jljH330UfaYeP6H+HzxYYYHHnggq9rzYAO1wdqz9qh/1p11BwAALH7CayoWK8fiY8WlTJo0KftvrLwq9zh2/NBfTqzmKqV9+/a13o/zuuuuK6hAO+qoo3Iq0OIH8lNOOaXsveV7/vnns82/YFFZe9Ye9c+6s+4AAIDFT3hNjZSrAKv6IXeFFVYoed7UqVPLvke54yuuuGKoTZ9//nnWy7OqVVddNevhmd9zdOTIkQXXx76pr776ajZH9+7dC47ffPPN1T4SDpWw9nJZe9QH6y6XdQcAANQ34TU1MmPGjJLHllxyyQV/XmWVVUqeN378+LLv8fXXX5c8Vq4KbmFcf/31BY9s//a3vy3o2/noo48WXLvRRhuFY445Jiy99NJhnXXWCWeddVbBOV9++WXWGxUWlbX3E2uP+mLd/cS6AwAAFgfhdRMW+3DG3pfxg2Z1PTnzH5MuZtlll13w527dupU8L364Lafc8XLz1tTYsWPDgw8+mDO20korhV/96lcF5w4fPrxgbOutt8553bt377DEEktUdC1Nm7Vn7VH/rDvrDgAAaHhyt5WnUbvtttvCiy++mG0yFb+qfij/29/+FjbeeOOy13/77bfhiy++KNmXM274NN+6665bcp5333234BHl/OOlbLDBBqEuK9COPPLIggq0+Aj0J598UnD96quvnvM69guN1Xf5m1uNHj261u6Zhsnay2XtUR+su1zWHQAA0BAJr5uQ+Gjyc889V/TYkCFDqv0g/+STT5Y89rOf/Sw0b/5TIX+5uV566aWy71PqkeNmzZpllV61IVa6DRo0KGesY8eOYd999y3aj3Tu3LkF4x06dKho7Lvvvlvk+6Vhs/Z+Yu1RX6y7n1h3AABAQ6VtSBNS7sN1rEKLlWml/PDDD+Gmm24qeXz33XfPed2jR4+w8sorFz33/fffDyNGjChZgRaPF7PeeuvV2uZVxSrQ/uu//qvoI9DTp08vOkerVq0KxvIr2KLvv/9+ke6Vhs/a+4m1R32x7n5i3QEAAA2V8LoJ2WabbcIyyyxT9Ni0adPCUUcdVXTjqLhh1UknnVTwaPB8cc5ddtmlYHzXXXcteS8XXXRRQc/R+PqCCy4oec2ee+4ZasO4cePC3//+95yxFVZYIRxwwAFFz2/btm3R8fwgICrWR7Vdu3YLfa80Dtbej6w96pN19yPrDgAAaMiE101IrJDab7/9Sh6PFWB77LFHuPLKK8Mrr7wS3njjjXDXXXdlH6Cfeuqpktf97ne/K1q9NWDAgKwnZjFx7rhJ1EMPPZT9Of43vv7Pf/5T9Pwll1wy9O/fP9SGG264oeBD+BFHHBHatGlT9Pyllloqe3y7kkeji40Ve6yapsXa+5G1R32y7n5k3QEAAA2ZntdNzNFHHx0eeeSRrP9lMZMnTw5XXXVVxfPFvp+lqre6dOmSBQd333130eOjRo0Kp556akXvc/jhh5esoKuJ+Jj4/fffnzO23HLLhV//+tclr2nRokXo2rVr+Pjjj3PG86vyYgVasc29unXrtsj3TcNn7Vl71D/rzroDAAAaNpXXTUys5rrkkkuK9qmsqfjY8eWXX56zaVW+k08+Oay11lqL9D7rrLNOOPLII0NtuPHGGwsec44hQanHpOfr1atXwdgLL7yQ8zpW7hV7hLrYtTQ91p61R/2z7qw7AACgYRNeN0GbbbZZ+Otf/7pIH+Y7duwYbr/99rDKKqtUGxzcdtttYc0111yo94nVX/GR59oIHmJv0/vuuy9nLFa2xUe9q5O/OVf05ptvhiuuuCKr3HvnnXfC+eefX3BO/Pn07t17Ee+cxsLa+4m1R32x7n5i3QEAAA2N8LqJ2mGHHbINnHr06FHja3/+85+HQYMGhe7du1d0/vLLLx/uuOOO0K9fvxq9T58+fcLAgQPDSiutFGqrAi1uxFXVYYcdloUN1dlqq63C+uuvXzB+9dVXZ8HIXnvtVXRzr1jhFh/BhvmsvR9Ze9Qn6+5H1h0AANDQNJs3b968xX0TLD6zZ88Ojz/+eLjzzjvD8OHDw9y5c4ueFz+Mxg+shxxySNhuu+0W+v3iJljxQ33cpGrOnDkFx+MmUT179gwHHXRQtmlWbRk/fnwWJPzwww85FWhDhgzJNqeqxEcffRT233//MGXKlIrO33rrrbPwoNjGV2DtWXvUP+vOugOoD599PCrMnVv4v/uwqJo3bxG6rLH24r6NZFl71BVrb/ESXrPA1KlTw7Bhw8K4ceOyx4LjB+327duH1VdfPWy44YahQ4cOtfZeEyZMCCNGjMg2k4rvFedeccUVsw/xtVV1VtVFF12UPcpd1YknnhiOO+64Gs3z/vvvhxNOOKFoxVlVsSrtvPPOq5VHv2n8rL3qWXvUNuuuetYdwMIRoFFXBGjlWXvUFWtv8RJe0+jF0CA+Ml61Ai0GB08//XQWVCxM5d4jjzwSBg8eHEaOHBkmTpwYWrZsmQUQ8bHvffbZx4ZVYO3BYmHdASx+AjTqigCtPGuPumLtLV7CawAAAKglAjTqigCtPGuPumLtLV42bAQAAAAAIDnCawAAAAAAkiO8BgAAAAAgOcJrAAAAAACSI7wGAAAAACA5wmsAAAAAAJIjvAYAAAAAIDnCawAAAAAAkiO8BgAAAAAgOcJrAAAAAACSI7wGAAAAACA5wmsAAAAAAJIjvAYAAAAAIDnCawAAAAAAkiO8BgAAAAAgOcJrAAAAAACSI7wGAAAAACA5wmsAAAAAAJIjvAYAAAAAIDnCawAAAAAAkiO8BgAAAAAgOcJrAAAAAACSI7wGAAAAACA5wmsAAAAAAJIjvAYAAAAAIDnCawAAAAAAktNycd9AUzb20w/D3DlzFvdt0Ag1b9EidFqt++K+jWRZe9QVa6806466Yt0BAEDjJbxejOKH+LlzfZCH+mbtQf2z7gAAAKgpbUMAAAAAAEiO8BoAAAAAgOQIrwEAAAAASI7wGgAAAACA5AivAQAAAABIjvAaAAAAAIDkCK8BAAAAAEiO8BoAAAAAgOQIrwEAAAAASI7wGgAAAACA5AivAQAAAABIjvAaAAAAAIDkCK8BAAAAAEiO8BoAAAAAgOQIrwEAAAAASI7wGgAAAACA5AivAQAAAABIjvAaAAAAAIDkCK8BAAAAAEiO8BoAAAAAgOQIrwEAAAAASI7wGgAAAACA5AivAQAAAABIjvAaAAAAAIDkCK8BAAAAAEiO8BoAAAAAgOQIrwEAAAAASI7wGgAAAACA5AivAQAAAABIjvAaAAAAAIDkCK8BAAAAAEiO8BoAAAAAgOQIrwEAAAAASI7wGgAAAACA5AivAQAAAABIjvAaAAAAAIDkCK8BAAAAAEiO8BoAAAAAgOQIrwEAAAAASI7wGgAAAACA5AivAQAAAABIjvAaAAAAAIDkCK8BAAAAAEiO8BoAAAAAgOQIrwEAAAAASI7wGgAAAACA5AivAQAAAABIjvAaAAAAAIDkCK8BAAAAAEiO8BoAAAAAgOQIrwEAAAAASI7wGgAAAACA5AivAQAAAABIjvAaAAAAAIDkCK8BAAAAAEiO8BoAAAAAgOQIrwEAAAAASI7wGgAAAACA5AivAQAAAABIjvAaAAAAAIDkCK8BAAAAAEiO8BoAAAAAgOQIrwEAAAAASI7wGgAAAACA5AivAQAAAABIjvAaAAAAAIDkCK8BAAAAAEiO8BoAAAAAgOQIrwEAAAAASI7wGgAAAACA5AivAQAAAABIjvAaAAAAAIDkCK8BAAAAAEiO8BoAAAAAgOQIrwEAAAAASI7wGgAAAACA5AivAQAAAABIjvAaAAAAAIDkCK8BAAAAAEiO8BoAAAAAgOQIrwEAAAAASI7wGgAAAACA5AivAQAAAABIjvAaAAAAAIDkCK8BAAAAAEiO8BoAAAAAgOQIrwEAAAAASI7wGgAAAACA5AivAQAAAABIjvAaAAAAAIDkCK8BAAAAAEiO8BoAAAAAgOQIrwEAAAAASI7wGgAAAACA5AivAQAAAABIjvAaAAAAAIDkCK8BAAAAAEiO8BoAAAAAgOQIrwEAAAAASI7wGgAAAACA5AivAQAAAABIjvAaAAAAAIDkCK8BAAAAAEiO8BoAAAAAgOQIrwEAAAAASI7wGgAAAACA5AivAQAAAABIjvAaAAAAAIDkCK8BAAAAAEiO8BoAAAAAgOQIrwEAAAAASI7wGgAAAACA5AivAQAAAABIjvAaAAAAAIDkCK8BAAAAAEiO8BoAAAAAgOQIrwEAAAAASI7wGgAAAACA5AivAQAAAABIjvAaAAAAAIDkCK8BAAAAAEiO8BoAAAAAgOQIrwEAAAAASI7wGgAAAACA5AivAQAAAABIjvAaAAAAAIDkCK8BAAAAAEiO8BoAAAAAgOQIrwEAAAAASI7wGgAAAACA5AivAQAAAABIjvAaAAAAAIDkCK8BAAAAAEiO8BoAAAAAgOQIrwEAAAAASI7wGgAAAACA5AivAQAAAABIjvAaAAAAAIDkCK8BAAAAAEiO8BoAAAAAgOQIrwEAAAAASI7wGgAAAACA5AivAQAAAABIjvAaAAAAAIDkCK8BAAAAAEiO8BoAAAAAgOQIrwEAAAAASI7wGgAAAACA5AivAQAAAABIjvAaAAAAAIDkCK8BAAAAAEiO8BoAAAAAgOQIrwEAAAAASI7wGgAAAACA5AivAQAAAABIjvAaAAAAAIDkCK8BAAAAAEiO8BoAAAAAgOQIrwEAAAAASI7wGgAAAACA5AivAQAAAABIjvAaAAAAAIDkCK8BAAAAAEiO8BoAAAAAgOQIrwEAAAAASI7wGgAAAACA5AivAQAAAABIjvAaAAAAAIDkCK8BAAAAAEiO8BoAAAAAgOQIrwEAAAAASI7wGgAAAACA5AivAQAAAABIjvAaAAAAAIDkCK8BAAAAAEiO8BoAAAAAgOQIrwEAAAAASI7wGgAAAACA5AivAQAAAABIjvAaAAAAAIDkCK8BAAAAAEiO8BoAAAAAgOQIrwEAAAAASI7wGgAAAACA5AivAQAAAABIjvAaAAAAAIDkCK8BAAAAAEiO8BoAAAAAgOQIrwEAAAAASI7wGgAAAACA5AivAQAAAABIjvAaAAAAAIDkCK8BAAAAAEiO8BoAAAAAgOQIrwEAAAAASI7wGgAAAACA5AivAQAAAABIjvAaAAAAAIDkCK8BAAAAAEiO8BoAAAAAgOQIrwEAAAAASI7wGgAAAACA5AivAQAAAABIjvAaAAAAAIDkCK8BAAAAAEiO8BoAAAAAgOQIrwEAAAAASI7wGgAAAACA5AivAQAAAABIjvAaAAAAAIDkCK8BAAAAAEiO8BoAAAAAgOQIrwEAAAAASI7wGgAAAACA5AivAQAAAABIjvAaAAAAAIDkCK8BAAAAAEiO8BoAAAAAgOQIrwEAAAAASI7wGgAAAACA5AivAQAAAABIjvAaAAAAAIDkCK8BAAAAAEiO8BoAAAAAgOQIrwEAAAAASI7wGgAAAACA5AivAQAAAABIjvAaAAAAAIDkCK8BAAAAAEiO8BoAAAAAgOQIrwEAAAAASI7wGgAAAACA5AivAQAAAABIjvAaAAAAAIDkCK8BAAAAAEiO8BoAAAAAgOQIrwEAAAAASI7wGgAAAACA5AivAQAAAABIjvAaAAAAAIDkCK8BAAAAAEiO8BoAAAAAgOQIrwEAAAAASI7wGgAAAACA5AivAQAAAABIjvAaAAAAAIDkCK8BAAAAAEiO8BoAAAAAgOQIrwEAAAAASI7wGgAAAACA5AivAQAAAABIjvAaAAAAAIDkCK8BAAAAAEiO8BoAAAAAgOQIrwEAAAAASI7wGgAAAACA5AivAQAAAABIjvAaAAAAAIDkCK8BAAAAAEiO8BoAAAAAgOQIrwEAAAAASI7wGgAAAACA5AivAQAAAABIjvAaAAAAAIDkCK8BAAAAAEiO8BoAAAAAgOQIrwEAAAAASI7wGgAAAACA5AivAQAAAABIjvAaAAAAAIDkCK8BAAAAAEiO8BoAAAAAgOQIrwEAAAAASI7wGgAAAACA5AivAQAAAABIjvAaAAAAAIDkCK8BAAAAAEiO8BoAAAAAgOQIrwEAAAAASI7wGgAAAACA5AivAQAAAABIjvAaAAAAAIDkCK8BAAAAAEiO8BoAAAAAgOQIrwEAAAAASI7wGgAAAACA5AivAQAAAABITsvFfQMAAAANzWeffRZef/318M0334TmzZuHFVZYIWyyySahU6dOCz3nvHnzwo033hhmzJixYKxFixbhyCOPDC1b+ugGADQ9/h8QAACwWEycODFst912OWFt1KdPn3DHHXfUynvMnDkz7LDDDmH8+PE54zFkfvrpp2s83/Dhw8NFF10Uhg0bVvR4DLBPPfXU0KtXrxrP/eSTT4a//OUvOWP9+/cXXAMATZa2IQAAwGJx++23FwTXte0f//hHQXC9sB555JFw4IEHlgyuo1iNPWDAgPDQQw/VuOr66quvzhmLVddHH330Qt8vAEBDJ7wGAADq3ejRo8Mtt9xS55Xd+ZXMC+vtt98Op512Wpg1a1a1586ePTuceeaZ4a233qp4/qeeeiqMGjUqZ2zXXXcNa6yxxkLdLwBAYyC8BgAA6tXUqVPDf//3f2ctPepKDJBPOeWUMGnSpFqZ77zzzsvmrKpNmzZh3333DXvuuWdWJZ3//vGaha26jn20jznmmFq4cwCAhkvzNAAAoN5Mnz49nHjiieG9996rs/eYM2dOVvk8dOjQWpkv3mvsdZ3vsssuy/ppRxtttFE499xzc46PGDEiu3adddYpO/+QIUPCu+++mzO28847hzXXXLNW7h8AoKFSeQ0AANSLb775Jhx88MHh3//+d51WdR977LE17jldzvPPP18w1rlz5wXBdfSrX/0qq8TO98ILL1Q7/zXXXJPzulmzZtn3AADQ1AmvAQCAOhdD3F/+8pdZNXJdiT2m99577/Dss8/W6rzvvPNOwdj666+f87p169ahR48eBeeNHDmy7NxPP/10wTk77bRT0bkAAJoabUMAAIA63TTxT3/6U3jwwQfrtNo69oweOHBgQV/q2vDFF18UjK288soFYx07diwYGzduXNm583tdq7oGAPiJ8BoAAKh1Y8eODffcc0+48847w/fff18n7zFhwoTw97//Pdx66621tjFjqXA8X9u2bQvG2rVrV9G188UK8bfffjtnrF+/ftX2yAYAaCqE1wAAQK3r27dvmDdvXp2+x3777Rc+//zzUNeKVXM3b17YgbFFixYFY7NmzSo571VXXVUwdtxxxy3UPQIANEZ6XgMAALWuXHDdsmXLcOSRR9bpe0THHHNMqA3FKqqLhdIzZswoGFtyySWLzvncc89lPbqr2n777cO66667SPcKANCYCK8BAIB6s8wyy4Sbbrop7L///nX2HrGlx5///Ofw+9//vlbmW3rppQvGirUpmTx5ckXXFut1Ham6BgDIJbwGAADqxY477hj++c9/hi222KLO3mPTTTcNDz/8cNhjjz1qbc611lqrYOyTTz4pGPvss88quvaFF14Iw4cPzxnbdtttQ8+ePRf5XgEAGhM9rwEAgDq19tprZ1XQO+ywQ529R5cuXcLxxx8ffvnLX4ZmzZrV6ty9evUqGBsxYkT49ttvF1RWjxkzJtukspJrVV0DAFRGeA0AANS6GCDHCusDDjgg7LTTTrUeKFcNh2MLkj333DO0atWqTt4j9qKOfa+///77nP7Wp512WjjnnHPCzJkzwxlnnFFwXfv27bNrq3rxxRfDsGHDcsa22mqroiE3AEBTJ7wGAABq3VNPPRU6d+5cp+8xcODAOn+P+ZsuHnTQQeH666/PGX/66aezr1LiNbH/dlVXXXVVwXmqrgEAitPzGgAAqHX1ESrXx3vMF1uSbLDBBhWfHyupjznmmJyxl156Kbz++us5Y7E6feONN661+wQAaEyE1wAAANVo3bp1uP322wvagBQTz7nllluya6rrdR1DcQAAitM2BAAAoAJLLbVUuO6667IK6ocffji89tpr4Ztvvglz584NK6ywQlZBHTeMjD2s873yyivhP//5T85Ynz59Qu/evevxOwAAaFiE1wAAADUQW33Er5qoSa/rESNGhAceeCALu7/66qtsQ8jll18+rLfeeqFfv37Z5pQtW/ooBwA0fv4fDwAAQB2KIfSrr76aMxYrrjfffPOcsRhSn3322WHQoEEFc3z55ZfZ15AhQ8INN9wQrrzyytCjR486v3cAgMVJz2sAAIA6VEnV9bx588Kxxx5bNLjO9/HHH4df//rX4aOPPqrV+wQASI3wGgAAoI7Evtgvv/xyzthGG20Uttxyy5yxO+64I7zwwgsVzztlypRwyimnZKE3AEBjJbwGAACoI1dffXW1Vddz5swJN998c8F5MeR+4oknsg0iDzrooILjI0eODP/+979r+Y4BANIhvAYAAKgDb7zxRnjxxRdzxnr16hW23nrrgp7Y48aNK7j+4osvDl27dg3LLbdcOOOMM0Lnzp0Lznn00Ufr4M4BANIgvAYAAKinquvY1zrfiBEjCsa6dOmSBdfzNW/evGCDx2j48OG1cq8AACkSXgMAANSyN998MwwdOjRnbP311w/bbbddwbnFNl5cffXVC8ZWW221grExY8aEuXPnLvL9AgCkSHgNAABQy6666qpqe13P99133xWMdejQoWCsffv2BWMxuJ46depC3ycAQMqE1wAAALUotgF54YUXcsbWXXfd0Ldv36LnT58+vWCsVatWBWOtW7cuev3333+/0PcKAJAy4TUAAMBiqrqO2rZtWzA2a9asgrGZM2cWvb5du3Y1vkcAgIZAeA0AAFBL3nrrrfDcc8/ljK299tqhX79+Ja8p1iKkWCuRKVOmFIzFjRyXWmqphb5fAICUCa8BAABqydVXX10wdswxx4RmzZqVvGbNNdcsuhFjJWNdu3bNAmwAgMbI/8sBAACoBSNHjgzPPPNMzliPHj3CzjvvXPa6DTfcsGDs888/Dx999NGC17Nnzw4vvfRSwXm9evVapHsGAEiZ8BoAAKCOel1XV3UdbbrppmHllVcuGD/11FPD6NGjw4QJE8L//u//hi+//LLgnN13330R7xoAIF0tF/cNAAAANHTvvPNOePrpp3PGunXrFnbZZZdqr23RokU44ogjwgUXXFDQP7vc9euvv374+c9/vgh3DQCQNpXXAAAAddTrutJ+1AcddFDYeuutK36/9u3bh0svvbTaqm4AgIZM5TUAAFDvOnfuHEaNGlXn71Mf7/Hee++FIUOGFGykuNtuu1U8Rwyhr7nmmnD22WeHQYMGlT03zn3llVcW3egRAKAxEV4DAAAsYtX1vHnzcsaOPvrorB1ITbRu3TpcdNFFYcCAAeGBBx4Ir776avj666/DDz/8EJZddtmw3nrrhX79+oX+/fuHVq1a1fJ3AQCQHuE1AADAIohV0LWpZ8+e2RcAQFOn5zUAAAAAAMkRXgMAAAAAkBzhNQAAAAAAyRFeAwAAAACQHOE1AAAAAADJEV4DAAAAAJAc4TUAAAAAAMkRXgMAAAAAkBzhNQAAAAAAyRFeAwAAAACQHOE1AAAAAADJEV4DAAAAAJAc4TUAAAAAAMkRXgMAAAAAkBzhNQAAAAAAyRFeAwAAAACQHOE1AAAAAADJEV4DAAAAAJAc4TUAAAAAAMkRXgMAAAAAkBzhNQAAAAAAyRFeAwAAAACQHOE1AAAAAADJEV4DAAAAAJAc4TUAAAAAAMkRXgMAAAAAkJyWi/sGAACAujH20w/D3DlzFvdt0Ag1b9EidFqt++K+DQCgkRNeAwBAIxWD67lzhdcAADRM2oYAAAAAAJAc4TUAAAAAAMkRXgMAAAAAkBzhNQAAAAAAyRFeAwAAAACQHOE1AAAAAADJEV4DAAAAAJAc4TUAAAAAAMkRXgMAAAAAkBzhNQAAAAAAyRFeAwAAAACQHOE1AAAAAADJEV4DAAAAAJAc4TUAAAAAAMkRXgMAAAAAkBzhNQAAAAAAyRFeAwAAAACQHOE1AAAAAADJEV4DAAAAAJAc4TUAAAAAAMkRXgMAAAAAkBzhNQAAAAAAyRFeAwAAAACQHOE1AAAAAADJEV4DAAAAAJAc4TUAAAAAAMkRXgMAAAAAkBzhNQAAAAAAyRFeAwAAAACQHOE1AAAAAADJEV4DAAAAAJAc4TUAAAAAAMkRXgMAAAAAkBzhNQAAAAAAyRFeAwAAAACQHOE1AAAAAADJEV4DAAAAAJAc4TUAAAAAAMkRXgMAAAAAkBzhNQAAAAAAyRFeAwAAAACQHOE1AAAAAADJEV4DAAAAAJAc4TUAAAAAAMkRXgMAAAAAkBzhNQAAAAAAyRFeAwAAAACQHOE1AAAAAADJEV4DAAAAAJAc4TUAAAAAAMkRXgMAAAAAkBzhNQAAAAAAyRFeAwAAAACQHOE1AAAAAADJEV4DAAAAAJAc4TUAAAAAAMkRXgMAAAAAkBzhNQAAAAAAyRFeAwAAAACQHOE1AAAAAADJEV4DAAAAAJAc4TUAAAAAAMkRXgMAAAAAkBzhNQAAAAAAyRFeAwAAAACQHOE1AAAAAADJEV4DAAAAAJAc4TUAAAAAAMkRXgMAAAAAkBzhNQAAAAAAyRFeAwAAAACQHOE1AAAAAADJEV4DAAAAAJAc4TUAAAAAAMkRXgMAAAAAkBzhNQAAAAAAyRFeAwAAAACQHOE1AAAAAADJEV4DAAAAAJAc4TUAAAAAAMkRXgMAAAAAkBzhNQAAAAAAyRFeAwAAAACQHOE1AAAAAADJEV4DAAAAAJAc4TUAAAAAAMkRXgMAAAAAkBzhNQAA/7+9+wCTqyofP35jQJCiIr2G0DsGIRSBUIL00Kt0CIIkgBCqVCmhCtJ7hyAQkN5BQg1dqlTpEAmgIE3F/J/v/T13/2fuzszO7M6duXfm+3mefXSX7M7d2XvOPec973mPJEmSJOWOwWtJkiRJkiRJUu4YvJYkSZIkSZIk5Y7Ba0mSJEmSJElS7hi8liRJkiRJkiTlzmTNfLHvvvsumjhxYjNfMtc++eyzaNJ3/2v1ZagN9ev/vej7U01o9WXklm1PWbHtVWa7U1Zsd9XZ9pQV215ltjtlxXZXnW1PWbHtdTfDDDNE/fv3j9oueE3geuWVV27mS0qSJEmSJEmSGmTcuHHRzDPPHDWDZUMkSZIkSZIkSblj8FqSJEmSJEmSlDsGryVJkiRJkiRJuWPwWpIkSZIkSZKUO/0mTZo0qVkv9t1338WHNkq1+vjjj6NNNtmk29fHjh0bzTjjjC25JqkT2Pak5rPdSa1h25Oaz3YntYZtT40ywwwzRP3794+aYbKoifilmnUSpdobnar3ktR8tj2p+Wx3UmvY9qTms91JrWHbU55ZNkSSJEmSJEmSlDsGryVJkiRJkiRJuWPwWpIkSZIkSZKUOwavJUmSJEmSJEm5Y/BakiRJkiRJkpQ7Bq8lSZIkSZIkSblj8FqSJEmSJEmSlDsGryVJkiRJkiRJuWPwWpIkSZIkSZKUOwavJUmSJEmSJEm5Y/BakiRJkiRJkpQ7Bq8lSZIkSZIkSblj8FqSJEmSJEmSlDsGryVJkiRJkiRJuWPwWpIkSZIkSZKUOwavJUmSJEmSJEm5Y/BakiRJkiRJkpQ7Bq8lSZIkSZIkSblj8FqSJEmSJEmSlDsGryVJkiRJkiRJuTNZqy9AqmbqqaeORowYUfbrkrJj25Oaz3YntYZtT2o+253UGrY9FVG/SZMmTWr1RUiSJEmSJEmSFLJsiCRJkiRJkiQpdwxeS5IkSZIkSZJyx+C1JEmSJEmSJCl3DF5LkiRJkiRJknLH4LUkSZIkSZIkKXcMXkuSJEmSJEmScsfgtSRJkiRJkiQpdwxeS5IkSZIkSZJyx+C1JEmSJEmSJCl3DF5LkiRJkiRJknLH4LUkSZIkSZIkKXcMXkuSJEmSJEmScmeyqAP8+9//jt58883ojTfeiP7xj39E//rXv+KvTzXVVNGss84aDRw4MJpnnnmifv36tfpSJeWM/YeUHduXJEmS6sXY8fXXX48++uij6Kuvvor69+/fNX6cb775ogEDBrT6EiU1UNsGr5kA33TTTdG9994bjR8/PvrPf/5T9d9PN9100aqrrhptvPHG0TLLLFPXa2277bbR448/Xtf30LlOPvnkcQc7/fTTR3PNNVf8uiussEK04IILVv3e008/PTrjjDOirI0YMSIaOXJk1EyHHXZY9Mc//rHr81deeaWpr99paBvbbbdd1+eDBw+OLr/88pZdz4EHHhjdcMMNXZ+PHj06bpPNZv/Rd/YfqsT21Xe2r//DfbTffvu17D2RJEnNw9hjzJgx0V133RV98sknVf/tDDPMEA0dOjTabLPNosUWW6xp16jOc8stt0T77rtv1+eXXXZZtOyyy7b0mtpR2wWvWXU799xzoyuvvDL64osvav6+zz77LLr++uvjj0GDBkWHHHJIpp3cd999F39888030aeffhq99tpr8UQ+CSCOGjUqWnLJJaNO8uijj5ZMjKVms/8oLvuP/LN9FVce2xf3xYknntjqy1AHBk5uvPHG6Mknn4zee++96PPPP48Xu2abbbZoiSWWiNZYY41olVVWib73PSszKv+eeuqpaJttton+97//tTRpJA8YYxx00EFdn2+00UbRcccd17LrSS++d3owjL72qKOOim6++eZo0qRJNX3PxIkTo6uvvjr+WH311aPDDz88mnnmmTO/VmXvww8/jP+XLPtWYxGFe1PZa6uRFQPJYcOGReecc07VifHUU08d/eAHP6j435955plo8803jy655JKoFXhQbbXVVvFDtFN8+eWX0W9/+9tWX4Y6mP1Hcdl/5J/tq7jy2L5YXNh///2jv//9762+FHUIgiBk99OPXXjhhdFf/vKXeMLKzhEW5ti6Tr+w++67R2uvvXY0bty4Vl+yVBULtAcffHBX4FrKq/fffz/aZJNN4t1W5QLX7Jj70Y9+FE077bQVFw5JQqD/fv7555twxcpy/MccYJ111oneeeedKA+OPPLIuPShstc2mddsHdlnn326bT9m2y8ZEGw5/tnPfhZvH5liiini/8YE+q233oruueee6LbbbitpADQMVp+px7nrrrvWdS0//elPow033LDqv2GgwLWyfZoO+ZFHHonrNYWvz4CCifyaa65Z8r38PvwetaBx8zvWc22JZm6vOeGEE+L3QWoF+4/y7D/UCLav8mxfvcPE9YgjjjA4qKZ59dVXox122KHHLeoJ2vXw4cMtZaNcO/XUU0ueQVIesThIfxqOAzkHhV0u66+/fjweYudLOIajFjZl6dgxRv+dIMC40047xQuNc845Z9N/F/XNc889F5ewe/nll6O8YI5y5513tvoyOkZbBK+ZwOy9997xhDJcgWOFbq+99qo4kWR1bvHFF48/GFxeeumlca1KOsnE73//+3h7cD3bdDhgisysevz3v/+NzjvvvOi0007rWlHkf9mCQJ1NrjWRXHOtDSocmPTm2rL22GOP5W47sjqH/Udl9h/qK9tXZbav+rGowLbfsWPHtvpS1EFbk3fcccduget55503GjJkSLxlmQzWl156Kbrvvvuib7/9tuvf0Gf98Ic/jLbffvsWXLkUVd3FxHNVyjv6UYLRCTKszzzzzIpnoJB5Pf/888cfjKnY8cf4LSw/csABB0RXXXVVU65fjUOpuDwFrikt+Lvf/a7Vl9FRCh+8JhuIw3rCifGUU04ZnXLKKdFqq61W88+ZbLLJop133jnO/mKQmkyQmaCywsMkkwl3Vnj9X//61/H//8Mf/tD19Y8//jiucbXHHntE7Yj3me3ItdauUmMR9MnDoVsJass1s76c/Uex2X/km+2r2PLWvigRsueee8ZBF6lZWCyhZEjYh9HvUBeY7L/QhAkT4pr4YZ3ak046Kd6RMWDAgKZet1QJCyzUdrZciPLun//8Z3xOSoI+t1rgOo2xIWM0khDOOuusklrvJFesvPLKmVy3OgPlQjh/Rc1T+JrXZD6FNWbopFhhq2diHGLbLtlcITKjOBygGdgCPffcc5d8jYl5u2JQz4E3SE8CpKzZfxSb/Ue+2b6KLU/tiwMjCRYauFYzPfHEE9EDDzxQ8rWTTz453jlSrk1wEBi7NBZaaKGur1He6Pzzz2/K9Uq1YBH2b3/7W6svI3d4xpDQk3y08rBGXH755SXX04mHNd59993xzpYEC4G1Bq5DJCCkFxD/9Kc/NeQa1ZkoFXLHHXd0fd7qcXKnKHTwmu2s999/f7fOafnll+/Tz6X+Jh+hZm2bJcOLQXGIQ2CSCWQ7ITMl3LKzxRZbtPR61FnsP4rN/iPfbF/Flpf29e6778bZ1tQbJtM9ZCarsjZmzJiSz3/xi19EQ4cOrfo9HDi77777lnzt9ttvL9mBIrUKB42GBx4bcFGePfvssyWf9yZwjcknnzzadNNNux0kLvW2XAhZ14kFF1wwTrBR9godvCa7IUTh/d12260hP5ti/qGnn3463g7YDIMGDSpbc6+dfP311yXbkakZyPZyqVnsP4rL/iP/bF/FlZf2dcMNN8SnyacPwuFQT7JfOahJygolFR588MGSr2299dY1fS+LdN///ve7PufwVzNd1WrsAqBcSLKQMuOMM/Z6J5TUDOFh2Qj71XqtuOKKJZ8zbkwfJC7VurM0OQeDXaXHHntsvECi7BW25jXZOI888kjJ1371q1/FmVGNwMre7LPPHtfs5GZceuml47pLbAnMWrkDrNIZR0XHxDM8NZhi99NMM00m98nzzz8fdzBffvll9OMf/zh+f5daaqnoJz/5SZQX1EtiBZjrpRYdB/zMN998caCk2oOa34nvY1JEwIHvm2eeeeLfjwl+M5GB+Nprr8WDAWqL8T4vsMAC0SKLLBLljf1Hsdl/5Jvtq9ia1b56wgF4BFtCHIbJVm6ej6effnrTr0mdlVm1xBJLxNv1aePUuq41649+iUPFwr7BuphqNQ6tCw++O+KII6J77rmnpdckVZM+c4MxeW8xbthwww3j8ft0000XTT/99HUvaHJYIHNd+nMC3/wMFviZF/CMaPRYmtdjXs0cn/EnpevI8OVQykZgjEUCCEkYPK+mmmqqeFGLcXW97085LNwmCSa8Z+xM4ucSG0iX4StSKZuwZCAJNYsttlhLr6mTFDZ4feutt5Z0aDSG9dZbr2E/n21Ue+21Vxw4XGmllZo6cSu3CtiXlca8IdgaHr6w0UYbNfTABDrKa665Jn6NStu56fTpaDj8a+2118582xyTbE5LDut38vDkYXH88cdHd911V9ktpQTLhg8fHneM4YOKBwCD0Ouvv76kFliC+5XT7XffffeqK4Hjx4+Ptttuu67PBw8eHNdYS+N9XH311bs+Z0ss9V9x7bXXxoeWvfrqq2Vfg4f6NttsE79OT/fxgQceGGfbJUaPHh3XoGs0+4/i6sT+o2hsX8WVdfvqrWmnnTYuO8NzLcvDOdU+gWfqo3PIJwtb9BGMueqZMBMouPDCC7t+HotltS7A0f/xuiGCAlKW92w1BP0uuuiirs/Z1UIJnDwGrwl0caDeBx98ECfDMBdiW/6SSy5ZNWjHGRs8w95+++34+1hAIomGRc9mZ0W++OKLcWIRf0/GLPQn/C3nnXfepl5H0aWTEggaMicOzxWoFWM15tz1ou+/+OKLoxtvvDH6/PPPy/4bEsZWWGGFeJzComctuKfD0mwkCiTB0QsuuKBbyZQE/QIlUEgK6Wn8m44/PPTQQ3FwOokjMF5PP6tAO+OQdMq2ERuoF+3w7LPPjuMMlbLb6de22mqreEdTtXH0tttuW3IIciiMYYB4RJa14eljWPRLDBw4MBo5cmRmr6c2Cl6nt/L9/Oc/jyfIjbTBBhtErVBu+3O7ZPkRaD344IO7TrimA2ULW6OQ7bf//vv3mAnH6z/33HPRb37zm3gwx+ElZPI1EwNG3otyD42wkzzxxBPjBxjXyKSd6+bhWO13JADHacwcNsTkK4vgCtdGEJsHYTUE6PkdCEpTZ4+/eavZfxST/Ucx2L6KKev21RvcN0zSeOa1y/usbHDfUmKGIAP9czpjLzHXXHPF9xST3lr7Je69eu4/Am/hrgECZ+yKk5p1z1YrF0LW6aGHHhq1SpiowqJOchAvSTAnnHBCPK8o917MMssscTAtffYEQW52DHF4GkHrNALHBPoIglVLNiAhKHzmsXhb7tDGdOIPB0mvu+668Wszz+EcjnD3Ujpgt8suu8S/Q0/Zs+mgXdaBuTwigDp27NiuzwmEkjhy+OGHR2uuuWamySPcg5deeml8b6V3gaWxa5pzXvggu5tAdL07oHkNSrbddNNNPS50UZqPAye53+pdECGBjlJw1eY69E3EELgHOXOk1rHgV199FY8jOeehJxy4TpIaCRME0hdeeOGoCOVCJk6cGP9/2u8xxxzT9J3una6QNa/pIDhwIsT2hnZBZxFi0NubFcY84gHPiniChw8r441w3XXXxaux5Tpjgr68TrmHHNkIm2++eZ+2ItWLBweZg2HgmmvjGssNZliFZXD717/+NX5oh78jvxvlQsph0EPguNF4wBJMSAeuCZJXWgWmrMjOO+9cdmDZTPYfxWX/kX+2r+LKsn31BsEAJoKHHHKIgWv1uL16yy23jPbee++4/6kUBARBJe71NdZYIx6LNRqT/lNPPbXkaxwy2+gFPBVbM+9ZklkodZDIY5969dVXxwF6Fr8rvRfUPyYwdvTRR3d97YEHHojPP7jlllsqzi8INhFkIuGm2vvcF+zU4+/JnKtS4DoJ2PH+E/ymHJ2q45Dc9LyS4C1zaHY+nnvuufF7mgXuNYKr5QLXzHennnrqst9HUJmgL9dZDwLK6cA1Y8xKc3yy+tmN9sUXX9T8GiySsSs7Pddhd1ul3QkEyM8///wefzYlFtlpXS5wzfyJ36Pca9BefvnLX3YrN5g39957b9zPJLhmFlfUXIUMXrMNJ70FoV0mj9Q0IogSorZRO2w3pOZRWJJirbXWigdijcDghYl2OCihg+Thwer+Cy+8EAdy6bTJRF5llVW6DWzozJPVtKzxQEwGWWzJ5sFAdjXXyPvE4IdtciG2EI0YMSLOqgaHrLBaSdCMgAqZCxwYQEZFekCYHCrQKGSbklkErpPBN6VPuBa+zvWw6pze7kXtSMqMtJL9RzHZfxSD7auYsmxfvcV7m36eSWks6pMhmV40CyfM5UrNMHknAzLdpvuCsRYL++EiF88Sxm5SK+5Zxi/MHxLMHRpZxqsRyHhmDMbid4JEHt6HckkDPKsIkJFAs8cee3TNi5L2RiCuHEokkEmbxU5UknPSSQwsWFUaH9BHMHdSdfwt+RtXGm+yqEMGNkHuww47LC4r0ohzSE455ZT4vgwx32V3JkFM/taMm/g7MmennnaIts1iSbKTrScERdk5kNw33E+UKQnn+GSAp3fw8LsSwK8nQM5YFpTTYaGVEh988Fq8fwSg0+3urLPOqhqMZ1cHCwqUywkNGTIknjcR4+D34DXYbcK/DYP/LOSwq4JFvTQyvynVwUe6hFL438r990Yh2ZA+KjHHHHNE++yzTyavpTYsG1LuxO4555wzKjoCJzSMdKCRTqToGJCE25F5APCQaQS2qLCdJVxx5zAAVgkXXXTRbiulnDbMB4M/riHZRscD4IADDuiqcZilpE41AxeCXiEeWsOGDeuqFZ2gPlVy4A9b7sjADjFAYhsaE362LCUrxfzvn//8527b7PoiyRbg/aWmVTpIzYCT+l1kG1HLKnwYsSJNjatWsf8oHvuP4rB9FU+W7UvKEuUCCOalM88Ye5AVxRZ7+m3ubQKGBCPGjBnT1d/zv9zrTESXW265ul6bn8kHr83CPKXg+PlhNiUBAH5+WNtUna2Z9ywLyeH4hrF5WK81L8+f8HlDYJ2sZEoI8D7wPpGNSq3iMLhNcJGAEr8j7YzFAN4/xm18zn8j+YB/F54NxNiupxq79SKomLR7SpsQeGTxl3kcSGzgdyAAGP7dx40bF3/k4VyJPCNASfCToGcl7Brjg5ItIMhLyTrORVl++eXr+nuTqHLOOeeUfI25NfPd9I4F2hRzdrLAKSmRvD7IJGbhKDkjqprk/qFdUxIkXQqEOT5tg+QZ5v9cYzivJlBeSwmV5HV22223OIAc7vbm+3ldSgpxAGUYnGWuRJIauwvK4f1KL9qyQ4J4RIjXIMDMIi9nWtEXJrtCaBujRo0qeQ8RnrlFcD3MtGcxrhmldNi5ES6K8Lu1Q+JKERUy87rcyk/Rs3M4/ZnOjVW2EA9hVhOLjpW9MKhBTadGnGKLK664oiSgQIdJZnA68JTG9jSuI8QqflJ7LWv8XdOB6xCn2g8aNKjb19kelw5ch3jwMIgLZVHSgO3k5QLXoZlmmilepU6vRodZEs1m/1E89h/FYfsqnizbl5QlAnHhhJIDFalRy0SaoEUSsGCCzmFpbNdnN1oYgGABkol/pYO4KqG/pw8ggMjWbbJBw8A1i0Cch0BZKakV9yzB0vAwdRbYq43ZW4HfhQB08j4QCOZgxuR9IPOWoHRymF2CQCUZz2SoE6CmvAMHaScBPOYoBD3TWakEksmYbaSk3fP3I4OW4HsSuE5qblOWjqBcugQEgUdVR1sgw7qeZIE333wz7pMZuxG8JukrDPhWQ78dGjBgQDwvqFZqh7kD9yi71kIktNRaHoY2QJutVsOaEirpBSj6k7AsUE84rJUze6rVXKdsGwtqoUplPZjTpxN3WJBKB67TWOhhJwTtI8EiRU9naTUb5evC8f9mm20W31NqjUJmXpfrBPJUS45JIKvk1bAKTmPnMDsCiy+99FK3f8N2Cjrrng50yDs6IspiJFg1ZJWyUcKtzmAVr9Zt6gyIWMVju0yCBxSn82atlu1i1IpNB8M4dKQnnHQcrlxmUc6A4F0tg2AefjzUk1ICZDBSty69xapZ7D+Kxf6jWGxfxZJ1+5KyvHcp+RQi0JdevE9jqzQTbYLKybiEMdJVV10VZ6PViv6hEsY8bIE2o1KtumdffvnlOIMzQRYq4/a8okxbtfeBQ5p55qYPTR4+fHic9VoJi0vslgsDYjzX691p0RMO1SToWakOMghKknEaHgL58MMPN/Q62hWBXTKCyWinTAflcGrFeI4sfD4oMUKbI7mq0hgxHTw98sgjq/5d0/+Wv2mSYc8CC7snuL97MnTo0Jp26bBoSoY2ddbD59ECCyxQ0zVyD9aCQDyB23DXSDmUAw3H/vRXtS7akijB9YSLUxxMSpvNAxYIw50hxD1YBFTrFDJ4nWzTDvEwr/W0TyamPWXVlTP77LNH9913X02DEz76gpVZAiBZ1e5pFrZ4sWUt2Y7MimF69bwvOASQAwsSrMDXW5KCFfIw+MTKIvdYuXpzjRzk1HI6cLhyn6xSzj///D1+X7iKiXoOc6gVW3VqwSSOsgGsgidaeUiJ/Udx2H8Uj+2rOLJuX1KW0guPLPbX2n+T0cpCJbvHwgkzgbBa++5KE/mkz6MtkUVHjdGeMtDUGZp1z3L/kWmalAthe3ue+3bGB9V2ooKMag5HI2EgQXY22dW1JPSEAcksEnq4jloCnARPw+A1wU1qEOdpkT/PWHQYO3ZsfL4S2bDUn67n70npEc6w4RDTcoftpbOLmavXk2XLjhsWWtjVmeAQ0lqC17XOqzFw4MCS4HWt82riD7XEEZLXCFV6Df4GoXqfd2R5U4YjGYs+9thjccnTRpb26S3OEgvniSxOVKqpr+YoZMpQuYcDtXjaAYE+Oj1qYzV6VbgVTjvttJKgZaO3rI0fP77kc4Ie9f58DhNgRTdcoS2XaddItdY/TA9man3gpANFtR4YUSsGkQyka8X2vVD6QLdmsv8oDvuP4rF9FUfW7UvK0qOPPtptJ0w9+Pe06QTlo9KHTVXD93KWCOUbWASiLAB1ekMEVWhXlEKQmnXPUoKEetkJ7lEyNfOK+rrpeUItCT1keNZSlqwZCT1hXd5qZptttm5ztFYm9BQVgWcWZAgMX3PNNXH95sGDB9cU8OT8KBaCwjZSaV6QLp1Ri3QQmkB7LfPwehI30u0lOeeqJ/XM3dMlbsrN3flaujQp7bIeBPzDhD4SK/Iwj2KXDNn6CWqO9+Z+UGMVMvO63IoHqyJFqqvJVmM6WBos2bSUUKAjZstutZpKRUJtqYsvvrjrc1YuG137L304GPXO6jXllFPG73/4EOPn1tv51qPSdqV6HySVZL2VnSyOeg4qCAfbWQTT62H/UQz2H8Vk+yqGZrQvKSvU9wzPKqDNspBYjxlnnDHu88PSbBw4RZZmLUaMGFH26xzAxgGoYV1jyjfQj7D4pc7UrHuWsUhY55lnV71B8mYrekIP4wLGCvXM5cL+oZUJPUVHO6JGOh+Un+BwToLFZNoTfOTMknJIqqDu880331ySgBIeBtjbeUH6e0hq4e/dU3JAepGlnnk1JTlr7UN6+xrl2g3vb3ggKlhQ6Gvwmf6SQzJbhQWusFwI5U0oN6PWK2Twmi0Pae+8807NDz+2V9Vy2jJbi3tzkAI1u8ItQUXFlrNwxaknrHgmW+JYASQTJdlCTqCTU3gbje1WoXoGDyEeKGHwiVOqw1VYSgPUgy001bIc2J7dG3nYQtOX66/3IZsF+4/msP/oTLav5ihC+5Kykg4wzDPPPDXXJA2xyBgGAtMLmr1BnWvOHGExKNzOfvzxx8clA1jwVOdpxj1LmRD69iQYStD2mGOO6TrEMK+KntBTT9Cx3FyulQk97Yb+lfrufLDrhd1l1GTm0NP0LkD+GzvpNt5444bOC8iKZqGFcjDhz+0peN2XuXWt8+re9Dk9ZbGnNeLcn/TfoV7UGacvrMcrr7zS9f85AJbzuRIErouUhNPOChm8LrfSypYFivjXgod4LTXGeOh7CnDv0HFRTzbB6iZ1jxst3bn1tuNPZwtmHXxKr2YWTbhKXTT2H/ln/1Fctq/8a1b7krLSyIXHLPpuavATNAwP2Cbr9u67747WX3/9hryGiqUZ9ywZ12HG48iRI7vVre2rvgaFyjGhp3UJPe2ORSKC2NQkZ6xDVnaIutnVgte9/dvyfWHwmoP/8jC3bvRrZDXfaeU8isxx6qonmL+ss846LbselSpkBIqVVibIbClIUNxd+UAWAKdih4EdsunGjBlT989Kfw9bcbLYjp8capLo1MPWOoH9R77ZfxSb7Svfiti+pJ6yvXqbTZblwiNlhhZaaKGSXTkcBmbwujNlfc8SIA4Pc6Q/pg57EZjQo6yx6HPBBRfEpZvYDRiWUCPzvdHZ+enDy7PO/m+VrEreUPe6VQ499NCSz9k5WssYOTzYERwiH54rww6TWmvjq7LC9rYrrbRSyeSYzoctWXPPPXdLr0v/13jDTpu6Qb095Tq9fZwag+HkOH1gAXWleiP9fZ763N7sP/LL/qP4bF/51cz2JeVd1guPbF0Pg9fhjgepkfcs/XgYSKJeLAfZ9SRdKodSiWHgiCD7sGHDGnDlUn1GjRoVvf322/GuFUowsbOA8zl6ixJp1MWm7FqCUiJkWyfnmaTrkTsvqK90DyV0Hn744ajIPvzww5LPzzjjjF79nEsuuaRb+T6D1x0cvCZ9/6KLLirZckM9x/RqiXqPuqB5rw2aDj6lO5xapb8vPNBg2WWX7XHLm4rF/iN79h+dy/aVvSK0L6lZffeXX37Zq5+T/r5G16OmfEiolq3jak9Z37PpccgVV1zRq59POa6wJBf3sMFrtQJnm7z77rslJej6ErzG0ksvXXVBiIO6w+A17WrQoEF1vQbBds4W6YR5Ae9XHssmUgomLAej9lHYPQxk96RPIaUYv1kNnYXT20MvvPBC3T+DVdd05oH1P9ub/Ydg/5EN25ekIiw8fvDBBxUDDN9880306quvRvfcc0+8GPfoo49GfdWu2XfKxz3bDASESOip50PqjQEDBpR8/vjjjze8HVLOIwzANmJekP4eMr7bNXhNTf2wJAq7P8JSGVKjFTbzGrvttlv8Ea6cUYyfSXIjTlP1AIXe6UumMnWFQj39nKWWWqrkcw4qmTBhQo8n+obuv//+kpOeyWKgTqHam/1HPtl/tAfbVz41s31JzToYlgVEMlLr7VtefPHFks/nmmuukoNNqZGaWHPNNevO+ksHKNlSrc7UjHtWaidkST/00ENdn/P/CYxyCGNvpZNNCFaHB38yL7j99tu7Pn/ggQei/fffv67XuPfee0s+X2KJJaJ2RdkQ3kMWehMs9NbzN2IORTkXgvzs9Jhjjjniklv8byv0dmy77bbbliywXHbZZfGYW41V2MxrrLrqqtGQIUNKvkbj4XTvvm7Ne/LJJ6NTTz21j1eorC2wwAIlgSZqedZ78NSVV15Z8vkyyyyTmxOslR37D9l/ZMf2JSkrTIzDbDkmvwQZ6sFCZToQGO4YSS/WcNgi2dj14HtCiy66aF3fr/aR9T3L4WD1ZkTzsdFGG5X8vNGjR5f8d36u1Arrrbde1K9fv5Kkhb6O/a699tqSz4cOHVry+YorrljyOTsG69l1Q/3sW2+9teRrBGLb/Zyb9LwoTOrpyR133BEnAvG+nXfeedFhhx1WsdZ4eD+oMxU6eJ0cUJHeivHEE09Em266aa+2+DEwOOSQQ+LVk/Spocoftqpss802JV8jUyY8IKcaAlVPPfVUydc233zzhl6j8sv+o7PZf2TL9iUpC0xg00GG9EJiT6666qqSw0unnXbakgy55ZZbruQARw43veWWW+paZEsHGlnUU2dqxj0rtRNK8K299tolX7vzzjujU045pVc/j4MEw3ruU0wxRbTFFlt0W2RKB2MPP/zwmmvUH3nkkSWB18knn7ztay8zj5pssv9fzOGNN96IzjrrrJq+l+fqSSedVPI1Fo4r7WANXwdhf6jOUPjg9SyzzBKfApquI8fptDvssEO04447xvXqqmVLcOM/9thj0QEHHBCfAsqqXHrFiCDHZpttltnvod7bcsstu04JTuot7bzzznEJgGp4gB199NElX2MQmF6FVfuy/5D9R3ZsX8J7770XT0bCD0oySH2x3XbbdQsW17pzhgXKCy+8sORrG264YcmumZlmmqlbxhz3LZPtnhC8SB9QS4Zs+iwAdZas71mp3VCyI30o4DnnnBPtuuuu0TvvvFPTz2DMyNiR0hSM8ROM9RmnplHyLqzjzJiVf/vZZ59VfA1K4xG4vu2220q+TrJFu5eLmm222brt4GDsf/755/f4nBwxYkT0/vvvl3x9zz33rPg9lBYJffrpp726ZhVXoWteJxgMXnrppXFnk76J2bLHB5PnRRZZJK7LQ7F+OiVORH3rrbfi02srbU8AHduxxx7b9ts+ilxviVW7XXbZpSuoMXHixDgDksDUJptsEk+W+Ztz+i+ZktQhSm+Fm2aaaaLjjjuu5IGl9mf/0dnsP7Jl+5KUhSWXXDJu92TTJVhQpD8hqFcJC5PDhw8vCWLQfxMMSdtrr73iOqvJs+Gjjz6K9thjjzirjO8ph36OIEl4aBVZt/vtt1+vf1e1h2bcs1I7mXXWWeMx+u67715y/1Nyh3a02mqrxecRUKuaf5uUlfj666/jMeSDDz4Y3XzzzSU1mTF48OC4L69Ua5sSd2effXbX15555plorbXWir/O/xKwBYuZXMu5557b7TUWXnjhqoHYdnLQQQfFi3FJTXFKvPB3o/43iSr0e8kz85NPPom/ziJEOnDN37JaElB6NyfzC3ZJJQsEJLyEO6bUftoieJ0MCK677ro40yEcFCToxAg6pLd4V8PWBLaT7LPPPhUHqcoHOkX+9gwCky0kPOQuv/zy+IO/JYeiUGu13EFf/H2ZjMw777wtuHq1mv1HZ7P/yJbtS1IWWDAk6MdkOMl+Y5cGNTTJeEvOICD4TGDh+uuvj0svhEGQZFs4mdZpiy22WDzxDjNex48fH22wwQZx4IPdICy4gUk4r0u2WTpDb++9944DIlLW96zUbijjQSCZ8V54Zgpt56677oo/khIdjNW//fbbeFxZCQfvnnnmmd1KUIRGjhwZffDBB9GNN95YUs/6+OOPjz8oOcLrVUquIBmDgHZ652G74n3nb0SGehiQJujPB5KxeqX3jLkCySjVsCAQeu655+L7g0Skr776Kp7H8XxW+2qb4DU4ofSiiy6KC76zmpNeAasVndG6664bZ4oNHDiw4depbGy99dbxPXDggQd2y/DjAUcmXzmLL754PJjkQaPOZf/R2ew/smX7ktRoBO8IQtAfEFhIcPgTH2ThMamlXin9eBr/ncDhsGHDKr7GqFGjog8//LBkOzilcMg0Az+fXTmVyh8RkOT6pGbds1K7IUBJIJngJFm75bDAE7apciUnaHfsYuhplyTZuyeccEI8zqS9phePCJDzUc76668fHzpIO+4kvFeUZ2GRgXJ/adV2UXI451FHHdWtLEi5f8eiAM/gBAt9yd+9t3MLFUdbBa8TTGzXWWedeDvy7bffHg8G2Abe04SY7c1rrLFG/P3tXp+oXQ0ZMiSuoXrxxRfH2Qrp7Sjh4I+/N5MKDoNwq78S9h+dy/4je7YvSY00aNCg6Jprrom3Z6cP22WnTKWFR7Yfc6gs286roX8/+eST44k5mWXpmvthJmCISTiLoekDwaSs71mpHVGqg12OtJmxY8fG48d33323x+/jEEaCnvTF9Y4fKVfCQhGve/fdd1dsm2RiM4fYaaed4vbdqaaffvq4lMe4cePiHUvsqEwH/sMFgpVXXjnafvvt42z4WvBcveSSS+IAOVnXaa+99lqffwflW79J5fZAtyG2frAaQ706Vn7IkmArB41s7rnnjmua0vGovXDi7SuvvBJvz+PvTqfH6cVkS6brJkmV2H90JvuP5rB9Seorgso33XRTfCYBNYIrTW/oUzbddNNoq622qrvkEM8Ddo6wyEk/VQ79FoES6hG70KZW37M9YYHlhhtu6Pp89OjR0cYbb9zQ12jUa3JgKgfBJTjsjfIOPSEZIdkpAQ6XY8dcb/8dpYPCwzepn0yJuVqx+BAmR5BJPMccc3T7dyRIPP74412fc58su+yyNb9OJyD54fXXX4/fTxYS2QFDggnthPd0oYUWKnsoY29QVpBzWKilTWkoMq/JriY4zryA0hkqxQ6Sp59+OpowYUL8ntHH8Z4NGDAgfs/60p+9/PLL0YsvvhjvluVvzvOW+QJn6Kh9dUzwWpIkSVL7BzSeffbZ6OOPP44z5aghPPPMM8f1Mgk09BUBEibkZP2xXZnFtemmmy4uH8XEOTk0TMrLPStJUtEZvJYkSZIkSZIk5Y6FOiVJkiRJkiRJuWPwWpIkSZIkSZKUOwavJUmSJEmSJEm5Y/BakiRJkiRJkpQ7Bq8lSZIkSZIkSblj8FqSJEmSJEmSlDsGryVJkiRJkiRJuWPwWpIkSZIkSZKUOwavJUmSJEmSJEm5Y/BakiRJkiRJkpQ7Bq8lSZIkSZIkSblj8FqSJEmSJEmSlDsGryVJkiRJkiRJuWPwWpIkSZIkSZKUOwavJUmSJEmSJEm5Y/BakiRJkiRJkpQ7Bq8lSZIkSZIkSblj8FqSJEmSJEmSlDsGryVJkiRJkiRJuWPwWpIkSZIkSZKUOwavJUmSJEmSJEm5Y/BakiRJkiRJkpQ7Bq8lSZIkSZIkSblj8FqSJEmSJEmSlDsGryVJkiRJkiRJuWPwWpIkSZIkSZKUOwavJUmSJEmSJEm5Y/BakiRJkiRJkpQ7Bq8lSZIkSZIkSblj8FqSJEmSJEmSlDsGryVJkiRJkiRJuWPwWpIkSZIkSZKUOwavJUmSJEmSJEm5Y/BakiRJkiRJkpQ7Bq8lSZIkSZIkSblj8FqSJEmSJEmSFOXN/wP+okL9oojOvgAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 1800x1200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bar_chart = percentage_comparison_bar_chart(\n",
    "    df,\n",
    "    metric_name=\"beat_comp_control_last\",\n",
    "    models=[\n",
    "        BenchmarkModelKey(\"mcp-010\", \"mcp-010\", \"val\"),\n",
    "        BenchmarkModelKey(\"gpt-4o-mini\", \"GPT-4o-mini\"),\n",
    "        BenchmarkModelKey(\"gpt-4o\", \"GPT-4o\"),\n",
    "        BenchmarkModelKey(\"gpt-4.1\", \"GPT-4.1\"),\n",
    "        BenchmarkModelKey(\"o3\", \"o3\"),\n",
    "        BenchmarkModelKey(\"o4-mini\", \"o4-mini\"),\n",
    "        BenchmarkModelKey(\"sonnet-4\", \"Sonnet-4\"),\n",
    "    ],\n",
    "    title=\"Win Rate\",\n",
    ")\n",
    "bar_chart.savefig(f\"{benchmarks_dir}/accuracy-comparison.svg\")"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": ".venv",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
